Development of interaction measures based on adaptive non-linear time series analysis of biomedical signals
Development of interaction measures based on adaptive non-linear time series analysis of biomedical signals
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DOI：
10.1515/bmt.2006.012
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发表时间：
2006-01-01
期刊：
影响因子：
--
通讯作者：
Witte, Herbert
中科院分区：
文献类型：
--
作者：
Leistritz, Lutz;Hesse, Wolfram;Witte, Herbert
两个信号分量之间相互作用的一个重要特征是相互作用的方向。最近，已经开发并应用了不同的方法来检测相互作用的方向。除了频率相关的方法，格兰杰因果关系是一个众所周知的频率无关的方法。一种流行的线性方法是基于基本过程的自回归建模，并在不同的过去假设下评估预测误差。在本研究中，这个线性概念被扩展到自激阈值自回归模型，它涵盖了更广泛的过程类别。给出了一种定义状态依赖的格兰杰因果关系的方法，并将其应用于模拟数据。
An important feature of interaction between two signal components is the direction of the interaction. Recently, different methods have been developed and applied for detecting the direction of interactions. Besides frequency-dependent methods, Granger causality is a well-known frequency-independent approach. One popular linear approach is based on autoregressive modeling of the underlying process and evaluates prediction errors under different past assumptions. In the present study, this linear concept is extended to self-exciting threshold autoregressive models, which cover a wider class of processes. An approach for the definition of a state-dependent Granger causality is given and applied to simulated data.